Multi-Frame Object Detection

Abstract

This thesis describes an object detection system that extracts and combines appearance information over multiple consecutive video frames, inherently gaining and analyzing information related to motion. Objects that exhibit characteristic motion over the course of multiple frames are able to be detected at smaller scales than is achievable using a single-frame detector. Our method builds on the detection work of Viola and Jones, with our extension being the added ability to combine information from multiple frames. Our implementation detects an object in synthetic images at very small scales, down to 3x3 pixels, and has a low false-alarm rate.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2012
Accession Number
ADA567167

Entities

People

  • Michael J. Laielli

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Autonomy
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Automata Theory
  • Computational Science
  • Computer Science
  • Computer Vision
  • Computers
  • Detection
  • Detectors
  • False Alarms
  • Feature Extraction
  • Information Science
  • Machine Learning
  • Neural Networks
  • Recognition
  • Remote Sensing
  • Video Frames
  • Warning Systems

Fields of Study

  • Computer science

Readers

  • Image Processing and Computer Vision.